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Mastering Databricks SQL Warehouse and Spark SQL

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Mastering Databricks SQL Warehouse and Spark SQL, available at $54.99, has an average rating of 4.35, with 198 lectures, based on 315 reviews, and has 2571 subscribers.

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You will learn about Setup Databricks SQL Warehouse Environment using Azure Databricks for hands-on Practice Getting Started with Databricks SQL for Data Analysis or Data Engineering Features of Databricks SQL Warehouse – Clusters, Query Editor, Visualizations and Dashboards, etc Overview of building reports and dashboards using Databricks SQL Creating Databases and Tables using Databricks SQL or Spark SQL Writing Basic Queries using Databricks SQL or Spark SQL DML to load data into Databricks SQL or Spark SQL Tables Advanced Operations such as Ranking and Aggregations using Databricks SQL or Spark SQL Processing Semi-Structured Data using Databricks SQL or Spark SQL In-depth Coverage about Delta Tables including all possible DML Operations such as Insert, Update, Delete, Merge, etc End to End Life Cycle of Data Analysis of Data in Files using Databricks (Uploading File to Databricks to Reports and Dashboards) This course is ideal for individuals who are Data Analysts and BI Developers who want to understand Databricks SQL or Spark SQL Queries to analyze the data or Data Engineers who would like to understand Databricks SQL or QA Analysts or Engineers who would like to understand Databricks SQL for the validation of the data or Business Analysts to analyze the Data in the Data Lake using Databricks SQL or Spark SQL Queries or BI Developers who want to understand how to connect BI Tools to Databricks SQL Endpoint and develop required reports and dashboards It is particularly useful for Data Analysts and BI Developers who want to understand Databricks SQL or Spark SQL Queries to analyze the data or Data Engineers who would like to understand Databricks SQL or QA Analysts or Engineers who would like to understand Databricks SQL for the validation of the data or Business Analysts to analyze the Data in the Data Lake using Databricks SQL or Spark SQL Queries or BI Developers who want to understand how to connect BI Tools to Databricks SQL Endpoint and develop required reports and dashboards.

Enroll now: Mastering Databricks SQL Warehouse and Spark SQL

Summary

Title: Mastering Databricks SQL Warehouse and Spark SQL

Price: $54.99

Average Rating: 4.35

Number of Lectures: 198

Number of Published Lectures: 198

Number of Curriculum Items: 198

Number of Published Curriculum Objects: 198

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

  • Setup Databricks SQL Warehouse Environment using Azure Databricks for hands-on Practice
  • Getting Started with Databricks SQL for Data Analysis or Data Engineering
  • Features of Databricks SQL Warehouse – Clusters, Query Editor, Visualizations and Dashboards, etc
  • Overview of building reports and dashboards using Databricks SQL
  • Creating Databases and Tables using Databricks SQL or Spark SQL
  • Writing Basic Queries using Databricks SQL or Spark SQL
  • DML to load data into Databricks SQL or Spark SQL Tables
  • Advanced Operations such as Ranking and Aggregations using Databricks SQL or Spark SQL
  • Processing Semi-Structured Data using Databricks SQL or Spark SQL
  • In-depth Coverage about Delta Tables including all possible DML Operations such as Insert, Update, Delete, Merge, etc
  • End to End Life Cycle of Data Analysis of Data in Files using Databricks (Uploading File to Databricks to Reports and Dashboards)

Who Should Attend

  • Data Analysts and BI Developers who want to understand Databricks SQL or Spark SQL Queries to analyze the data
  • Data Engineers who would like to understand Databricks SQL
  • QA Analysts or Engineers who would like to understand Databricks SQL for the validation of the data
  • Business Analysts to analyze the Data in the Data Lake using Databricks SQL or Spark SQL Queries
  • BI Developers who want to understand how to connect BI Tools to Databricks SQL Endpoint and develop required reports and dashboards

Target Audiences

  • Data Analysts and BI Developers who want to understand Databricks SQL or Spark SQL Queries to analyze the data
  • Data Engineers who would like to understand Databricks SQL
  • QA Analysts or Engineers who would like to understand Databricks SQL for the validation of the data
  • Business Analysts to analyze the Data in the Data Lake using Databricks SQL or Spark SQL Queries
  • BI Developers who want to understand how to connect BI Tools to Databricks SQL Endpoint and develop required reports and dashboards

Databricks SQL Warehouse is relatively new technology to build Data Lakehouse or Data Warehouse leveraging powerful Apache Spark Engine where the analytics can be built at scale. As part of this comprehensive course, you will learn all key skills required to master Databricks SQL Warehouse including Spark SQL as the SQL in Databricks SQL Warehouse is based on Spark SQL.

This course also covers most of the curriculum relevant to clear the Databricks Certified Data Analyst Associate Exam offered by Databricks itself.

Here are the high-level details related to this course. This is a beginner level course where you will be able to not only learn syntax and semantics of Databricks SQL or Spark SQL, you will also understand the concepts of the same.

  • Setup Course Material and Environment for Databricks SQL Warehouse

  • Managing Databases using Databricks SQL Warehouse

  • Manage Delta Tables in Databricks SQL Warehouse

  • Setup Data Set for Databricks SQL Views and Copy Commands

  • Databricks SQL or Spark SQL Queries to Process Values in JSON String Columns

  • Copy Data into Delta Tables in Databricks SQL Warehouse

  • Insert or Merge Spark SQL or Databricks SQL Query Results or View into Delta Tables

  • Merge Spark SQL or Databricks SQL Query Results and Data from Delta Table with Delete into Delta Tables

  • Basic SQL Queries using Spark SQL or Databricks SQL

  • Performing Aggregations using Group By and filtering using Having leveraging Spark SQL or Databricks SQL

  • Aggregations using Windowing or Analytical Functions including Cumulative Aggregations using Spark SQL or Databricks SQL

  • Ranking using Windowing or Analytical Functions using Spark SQL or Databricks SQL

  • Dealing with different file formats such as parquet, json, csv, etc using Spark SQL or Databricks SQL

  • All Important types of Joins such as Inner, left or right outer, full outer using Spark SQL or Databricks SQL

  • Visualizations and Dashboards using Databricks SQL Warehouse

We have also provided quite a few exercises along with solutions with explanations through the course.

Key Takeaways of Mastering Databricks SQL and Spark SQL using Databricks SQL Warehouse

  • Setup Environment to learn Databricks SQL and Spark SQL using Azure

  • Support via Udemy Q&A backed by our expert team

  • Data Sets and Material via GitHub Repository along with instructions to practice Databricks SQL or Spark SQL

  • Life Time Access to High Quality Video Lectures to learn Databricks SQL and Spark SQL

Course Curriculum

Chapter 1: Introduction to Mastering Databricks SQL Warehouse and Spark SQL

Lecture 1: Introduction to Mastering Databricks SQL Warehouse and Spark SQL

Chapter 2: Setup Databricks Environment using Azure

Lecture 1: Introduction to Setup Databricks Environment using Azure

Lecture 2: Signup for Azure Portal

Lecture 3: Setup Azure Databricks using Azure Portal

Lecture 4: Launching Azure Databricks Environment

Lecture 5: Create Single Node Databricks Cluster

Lecture 6: Editing Databricks Clusters using Databricks UI

Lecture 7: Getting Started with Databricks Notebooks

Lecture 8: Create Databricks SQL Warehouse

Lecture 9: Increase Quota to Create Databricks SQL Warehouse Cluster

Lecture 10: Run Queries using Databricks SQL Warehouse

Lecture 11: Overview of Uploading Data using Databricks SQL Warehouse UI

Lecture 12: Review Data Explorer of Data Science and Engineering Environment

Lecture 13: Analyze Sales Data using Databricks Notebooks

Lecture 14: Terminate Databricks Data Science and Engineering Clusters

Lecture 15: Terminate Databricks SQL Warehouse Clusters

Lecture 16: Delete Azure Databricks Workspace

Chapter 3: Setup Course Material and Environment for Databricks SQL

Lecture 1: Install Databricks CLI using Python 3 Pip Command

Lecture 2: Configure Databricks CLI using Token and Profile

Lecture 3: Setup Git Repository for Material and Data Sets related to Databricks SQL Course

Chapter 4: Getting Started with Databricks SQL

Lecture 1: Overview of Databricks SQL Platform – Introduction

Lecture 2: Run First Query using SQL Editor of Databricks SQL

Lecture 3: Overview of Dashboards using Databricks SQL

Lecture 4: Overview of Databricks SQL Data Explorer to review Metastore Database and Tables

Lecture 5: Use Databricks SQL Editor to develop scripts or queries

Lecture 6: Review Metadata of Tables using Databricks SQL Platform

Lecture 7: Overview of loading data into retail_db tables

Lecture 8: Configure Databricks CLI to push data into Databricks Platform

Lecture 9: Copy JSON Data into DBFS using Databricks CLI

Lecture 10: Analyze JSON Data using Spark APIs

Lecture 11: Analyze Delta Table Schemas using Spark APIs

Lecture 12: Load Data from Spark Data Frames into Delta Tables

Lecture 13: Run Adhoc Queries using Databricks SQL Editor to validate data

Lecture 14: Overview of External Tables using Databricks SQL

Lecture 15: Using COPY Command to Copy Data into Delta Tables

Lecture 16: Manage Databricks SQL Endpoints

Chapter 5: Managing Databases using Databricks SQL Warehouse

Lecture 1: Review Databases using Databricks SQL Data Explorer

Lecture 2: Create Database or Schema using Databricks SQL

Lecture 3: Using IF NOT EXISTS while Creating Databases using Databricks SQL

Lecture 4: Listing or Showing Databases and Getting Metadata of Databases using Databricks

Lecture 5: Understand Default Location of Databricks SQL Database or Schema

Lecture 6: Create Database or Schema using Location in Databricks SQL Warehouse

Lecture 7: Drop Databases in Databricks SQL Warehouse

Lecture 8: Alter Database in Databricks SQL Warehouse

Lecture 9: Comments on Databases in Databricks SQL Warehouse

Chapter 6: Manage Delta Tables in Databricks SQL Warehouse

Lecture 1: List Databases and Save Databricks SQL Script

Lecture 2: Create Table using Delta Format in Databricks SQL Warehouse

Lecture 3: Understand Location and Using Clause to specify File Format for Databricks

Lecture 4: Create External Table using Delta Format in Databricks SQL Warehouse

Lecture 5: Drop External Table and Delete Folder in Databricks SQL Warehouse

Lecture 6: Overview of DML or CRUD Operations using Databricks SQL

Lecture 7: Insert Records into Databricks SQL Warehouse table

Lecture 8: Insert Multiple Records into Databricks SQL Warehouse table

Lecture 9: Update Existing Records in Databricks SQL Warehouse table

Lecture 10: Update Existing Records in Databricks SQL Warehouse table based on Null Values

Lecture 11: Delete Existing Records in Databricks SQL Warehouse table

Lecture 12: Cleanup Users Tables from Databricks SQL Warehouse Database or Schema

Chapter 7: Setup Data Set for Databricks SQL Views and Copy Commands

Lecture 1: Getting Started with Databricks fs Commands using Databricks CLI

Lecture 2: Create Folder in DBFS using Databricks CLI Commands

Lecture 3: Copy Files from Local File System into DBFS using Databricks CLI Commands

Lecture 4: Overwrite Files while Copying into DBFS using Databricks CLI Command

Lecture 5: Understand Course Catalog Data in the files uploaded to DBFS

Lecture 6: Options to Analyze Data using Databricks SQL Queries

Lecture 7: Run Select Queries using DBFS Path in From Cluase

Lecture 8: Run Queries using Temporary Views in Databricks SQL

Lecture 9: Run Queries using External Tables in Databricks SQL

Chapter 8: Queries to Process Values in JSON String Columns

Lecture 1: Queries to Process Values in JSON String Columns

Lecture 2: Get Distinct and Count based on Key using Course Catalog Data

Lecture 3: Filter Data using Basic Databricks SQL Queries using Course Catalog Data

Lecture 4: Exploring Functions using Databricks SQL

Lecture 5: Understand Record Column Values in Course Catalog Table

Lecture 6: Processing JSON String Values using Databricks SQL Queries

Lecture 7: Process Instructors JSON Records using Databricks SQL Queries

Lecture 8: Create View for Instructors using Databricks SQL Queries

Chapter 9: Copy Data into Delta Tables in Databricks SQL Warehouse

Lecture 1: Create Delta Table for Course Catalog Data Set

Lecture 2: Get File Names along with Data using Databricks SQL Queries

Lecture 3: Overview of Databricks SQL COPY Command

Lecture 4: Copy Data from single file into Delta Tables using Files

Lecture 5: Copy Data from multiple files into Delta Tables using Files

Lecture 6: Copy Data from multiple files into Delta Tables using Pattern

Lecture 7: Create Course Catalog Table in Databricks SQL Warehouse with additional Column

Lecture 8: Copy Data from Files using Queries into Delta Tables

Lecture 9: Validate Course Catalog Table in Bronze Layer

Chapter 10: Insert or Merge Query Results or View into Delta Tables using Databricks SQL

Lecture 1: Introduction to Insert or Merge Query Results or View into Delta Tables using D

Lecture 2: Create Course Catalog and Instructors Tables using Databricks SQL

Lecture 3: Copy Data into Course Catalog Table from JSON Files using Databricks SQL

Lecture 4: Insert Query Results into Delta Table using Databricks SQL

Lecture 5: Exercise to Create Courses Table and Insert Data

Lecture 6: Copy Instructors Data into Course Catalog Table from new file

Lecture 7: Understand the Concept of Merge or Upsert in DML or CRUD Operations

Instructors

Rating Distribution

  • 1 stars: 7 votes
  • 2 stars: 7 votes
  • 3 stars: 36 votes
  • 4 stars: 130 votes
  • 5 stars: 135 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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